Event Characterization Fusing Hard and Soft Data via Semantic Models
Abstract
This work explores a new paradigm for event characterization using hard and soft data. Here, harddata is data yielded by physics-based sensing mechanisms such as a telescopes or radar. Softinformation is denoted by human-derived or semantically-derived information, such as HUMINTand OSINT. By fusing both hard and soft sources, a more accurate and reliable system can bedeveloped to characterize events, and also predict events in order to protect assets by directlycommanding and controlling space assets to mitigate intentional and non-intentional threats. Thefocus of the work is specifically on space events, but the framework can be modified to othermilitary domains involving autonomous systems, such as swarms of unmanned or remotely pilotedvehicles.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Sep 19, 2018
- Source ID
- FA95501810279
Entities
People
- John Crassidis
Organizations
- Air Force Office of Scientific Research
- Research Foundation for the State University of New York
- United States Air Force